Finite element simulation analysis of laminated sheets in deep drawing process using response surface method

Nejad, Seyyed Joneid Hasan; Hasanzadeh, Rezgar; Doniavi, Ali; Modanloo, Vahid

doi:10.1007/s00170-017-0780-5

Cited by 31 publications

(16 citation statements)

References 11 publications

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“…The Box-Behnken design (BBD) of the RSM was used to design the experiments, through Design-Expert software (version 10.0). The quadratic full equation (shown in equation (4)) which had been proved to be utility in the literatures, 33-36 was chosen to construct the model of response and variables.where Y is response value, β 0 is a constant, and β i , β ii , and β ij are the linear, quadratic, and interactive coefficients, respectively. X i and X j are variables values.…”

Section: Methodsmentioning

confidence: 99%

Investigation into the effects of foaming variables on the cellular structure and expansion ratio of foamed TPU using response surface methodology

Wang

2023

Journal of Cellular Plastics

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Thermoplastic polyurethane elastomer (TPU) foams were prepared using the high-pressure autoclave with supercritical fluid carbon dioxide (SC-CO2). The effects of foaming variables (i.e. saturation temperature, saturation pressure, and depressurization rate) on cellular structure and expansion ratio were investigated. The model between expansion ratio and foaming variables was constructed using the Box-Behnken design (BBD) of response surface methodology (RSM), and analysis of variance (ANOVA) was conducted to evaluate the validity and significance of the model. Finally, the interactive effects of foaming variables on the expansion ratio were investigated, and the expansion ratios of maximum and center point from numerical model were verified by experiment. The result showed higher saturation pressure and depressurization rate resulted in the more uniform cellular structure and higher cell density, however the higher saturation temperature resulted in the bigger cell and nonuniform structure. The ranges of average cell diameter and cell density were 15.26–45.4 μm and 0.32 × 108 to 6.24 × 108 cells/cm3, respectively. The model obtained using BBD of RSM was valid to predict the expansion ratio in the design window. The saturation temperature was the most important factor influencing the expansion ratio. With the increase of saturation temperature, the expansion ratio always increases in the design window. The maximum expansion ratio from numerical optimization was 4.91, which was located at saturation temperature 190°C, saturation pressure 12.51 MPa, and depressurization rate 5 MPa/s, and the corresponding experiment value was 4.56. The error between them was 7.13%.

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Section: Methodsmentioning

confidence: 99%

Investigation into the effects of foaming variables on the cellular structure and expansion ratio of foamed TPU using response surface methodology

Wang

2023

Journal of Cellular Plastics

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“…Also, the dwell time selection above 20 seconds caused the aluminum side to fracture due to overheating. Nowadays, design of experiment (DOE) methods have a broad range in engineering applications [10][11][12][13][14]. Taguchi method is one of the most popular DOE methods [15][16][17][18].…”

Section: Methodsmentioning

confidence: 99%

Finite Element Simulation and Experimental Test of Ovine Corneal Tissue Cutting Process in Cataract Surgery Operation

Band

Arbabtafti

Nahvi

et al. 2021

IJE

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“…Various authors have studied the effects of these process parameters using full factorial (Gebisa and Lemu, 2019; Taylor et al , 2019) DoE, which involves running experiments with all possible combination of factors. While full factorial DoE are the most accurate, predictive models, such as Response Surface Methodology (Hasan Nejad et al , 2017; Srinivasan et al , 2020a; Kamoona et al , 2017) and Taguchi DoE (Mostafa et al , 2018; Vishwas et al , 2018; Camposeco-Negrete, 2020; Raffic et al , 2019; Zaman et al , 2019; García-García et al , 2019; Chung Wang et al , 2007) minimizes the number of experimental runs which can significantly reduce cost and time required to conduct the experiments. However, to our knowledge, no published article has reported a comparison between a predictive DoE method with full factorial DoE to verify their accuracy in determining the effects of FFF process parameters on properties of printed parts.…”

Section: Literature Reviewmentioning

confidence: 99%

Fused filament fabrication of nylon 6/66 copolymer: parametric study comparing full factorial and Taguchi design of experiments

Rashed

Kafi

Simons

et al. 2022

RPJ

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Purpose Process parameters in Fused Filament Fabrication (FFF) can affect mechanical and surface properties of printed parts. Numerous studies have reported parametric studies of various materials using full factorial and Taguchi design of experiments (DoEs). However, a comparison between the two are not well-established in literature. The purpose of this study is to compare full factorial and Taguchi DoEs to determine the effects of FFF process parameters on mechanical and surface properties of Nylon 6/66 copolymer. In addition, perform in-depth failure mechanism analysis to understand why the process parameters affect the responses. Design/methodology/approach A full factorial DoE was used to determine the effects of FFF process parameters, such as infill density, infill pattern, layer height and raster angle on responses, such as compressive strength, impact strength, surface roughness and manufacturing time of Nylon 6/66. Micro-computed tomography was used to analyse the impact test samples before and after impact and scanning electron microscope was used to understand the failure mechanism of infill and top layers. Differential scanning calorimetry (DSC) scans of infill and top layers were then taken to determine if a variation in crystallinity existed in different regions of the build. Findings Analysis of variance and main effects plots reveal that infill density has the greatest effect on mechanical and surface properties while manufacturing time is most affected by layer height for the polymer used. A 20% reduction in infill increased impact strength by 19% on average, X-ray images of some of the samples before and after impact tests are presented to understand the reason behind the difference. Moreover, DSC revealed a difference in the degree of crystallinity between the infill and top layers for 80% infill density samples. In addition, Taguchi DoE is realized to be a more efficient technique to determine optimum process parameters for responses that vary linearly as it reduces experimental effort significantly while providing mostly accurate results. Originality/value To the author’s knowledge, no published paper has reported a comparison between predictive DoE method with full factorial DoE to verify their accuracy in determining the effects of FFF process parameters on properties of printed parts. Also, a theory was developed based on DSC results that as the infill is printed faster, it cools slowly compared to the top layers, and hence the infill is in a less crystalline state when compared to the top layers. This increased the ductility of the infill (of 80% infill samples) and thus improved impact absorption.

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Finite element simulation analysis of laminated sheets in deep drawing process using response surface method

Cited by 31 publications

References 11 publications

Investigation into the effects of foaming variables on the cellular structure and expansion ratio of foamed TPU using response surface methodology

Investigation into the effects of foaming variables on the cellular structure and expansion ratio of foamed TPU using response surface methodology

Finite Element Simulation and Experimental Test of Ovine Corneal Tissue Cutting Process in Cataract Surgery Operation

Fused filament fabrication of nylon 6/66 copolymer: parametric study comparing full factorial and Taguchi design of experiments

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